Modern organizations depend on hundreds, sometimes thousands, of SaaS applications to power their operations. While these tools accelerate productivity and innovation, they also create sprawling, complex ecosystems of user identities, data flows, and third-party integrations. For CISOs, CIOs, and SOC teams, enforcing strong security controls in this environment has become a non-negotiable priority.
That’s where Zero Trust SaaS comes into play. By applying Zero Trust principles to SaaS environments, organizations assume breach by default and continuously verify every access request, whether it’s from an employee, third-party app, or machine identity. However, these principles only work if you have visibility into what—and who—is accessing your SaaS stack. Without it, Zero Trust becomes just another checkbox.
SaaS visibility and access control lay the groundwork for effective Zero Trust SaaS implementation. Let’s take a look at some real-world incidents that underscore the risks of poor visibility, and show how turning insights into action can significantly strengthen your SaaS security posture.
Why you can’t enforce Zero Trust without visibility
At the core of any Zero Trust model is the “assumption of breach.” No user or system is inherently trusted, and every access request must be continuously validated. But in practice, applying this to SaaS is nearly impossible without visibility. Most enterprises operate with fragmented SaaS ecosystems comprising hundreds of applications, each with its own identity store, access protocols, and sharing mechanisms.
Traditional IAM solutions often fail to provide holistic oversight across this surface area. Without continuous discovery of connected apps, detailed inventories of users (including service accounts and guest collaborators), and visibility into tokenized access and API integrations, Zero Trust policies become theoretical rather than enforceable. Blind spots in this layer not only weaken policy enforcement, they create entry points for lateral movement and data exfiltration that remain undetected.
According to the 2025 Verizon Data Breach Investigations Report, 30% of all breaches involved third-party relationships, up from 15% the previous year, often through credential exposures or misconfigurations. These are precisely the areas that evade detection without comprehensive SaaS visibility.
Take the 2023 CircleCI breach, for example. Attackers gained access to a CircleCI engineer’s laptop via malware, extracting session tokens that bypassed multifactor authentication. Because CircleCI relied on a SaaS CI/CD pipeline that lacked continuous session monitoring, the threat actor had prolonged access without triggering alerts. Visibility gaps like these illustrate the urgent need to monitor both users and SaaS-to-SaaS interactions continuously.
In practice, Zero Trust SaaS must begin with a clear, continuous view of:
- All SaaS applications in use, sanctioned or not. Visibility must extend beyond officially approved tools to include shadow IT. These unsanctioned services often lack security oversight, making them prime targets for threat actors exploiting weak configurations or unmanaged access tokens.
- All human and non-human identities interacting with SaaS. This includes employees, contractors, service accounts, and machine identities like bots or automated integrations. Each identity presents a potential attack vector, especially if entitlements are excessive, dormant, or poorly monitored across platforms.
- All data flows between SaaS platforms and external services. Understanding which applications exchange data, along with how they do it, is crucial for detecting anomalies and preventing data leakage. This includes both user-initiated actions and automated transfers via APIs or third-party integrations, which often occur without visibility from traditional security tools.
Without this level of attention, enforcing Zero Trust policies is like trying to lock your front door while leaving every window open.
Turning visibility into action: real Zero Trust enforcement
Visibility is only the first step. For a Zero Trust SaaS model to be effective, organizations must convert insights into enforceable policies. This includes granular SaaS access control at the user, app, and data level.
Start by applying least privilege principles. If an employee only needs access to a CRM’s read-only analytics, there’s no reason for them to have admin credentials, write permissions, or access to export functions. Similarly, API tokens and OAuth scopes should be tightly configured to permit only the exact set of actions required, with token rotation policies enforced at regular intervals to mitigate the risk of credential leakage. Expired or unused tokens should be automatically revoked to close off unnecessary attack surfaces.
Role-based access control (RBAC) and attribute-based access control (ABAC) are essential to enforce these boundaries at scale. RBAC assigns permissions based on predefined job functions, while ABAC adds context like device posture, login time, or user location. However, both models require integration with a continuously updated SaaS asset inventory to remain accurate and effective.
If a terminated employee retains active OAuth tokens linked to Google Workspace, Slack, or GitHub, your Zero Trust enforcement has a critical blind spot. Token misuse, especially through service accounts, can go undetected if visibility is limited to user-facing interfaces.
Wing Security’s automated SaaS access control capabilities extend these models with contextual logic, enabling enforcement based on real-time signals like behavioral anomalies or geolocation mismatches. SOC teams can define escalation thresholds, trigger automated revocations, and dynamically quarantine suspicious accounts. By linking access decisions to identity lifecycle changes and SaaS telemetry, organizations shift from reactive cleanup to proactive Zero Trust enforcement.
Here’s a quick checklist that covers the key points. Enforcement of Zero Trust principles in SaaS environments should include:
- Automated onboarding and offboarding tied to identity lifecycles. This ensures that user access to SaaS applications is provisioned and de-provisioned in sync with identity provider events, reducing the window for exploiting orphaned or stale accounts.
- Contextual access decisions based on device posture and user behavior. Access is granted or denied dynamically based on real-time signals like OS patch level, geolocation, IP reputation, or behavioral anomalies such as atypical login times or lateral movement patterns.
- Continuous session monitoring and token usage tracking. Active sessions are monitored for behavioral anomalies, and token-based authentications (like OAuth or API keys) are tracked for misuse, overuse, or suspicious patterns across multiple applications.
- Real-time policy enforcement and remediation workflows. Policies are not only defined but enforced via automated responses such as immediate session termination, access revocation, or triggering of incident response playbooks when violations occur.
For a more technical breakdown, see our blog on minimizing identity-based attacks in SaaS.
Managing third-party and app-to-app risk
Modern SaaS environments are not just user-centric—they’re app-centric. Today’s platforms rely heavily on interconnected services, where both third-party tools and internal app-to-app integrations access and process critical data through APIs, webhooks, and OAuth connections. These non-human relationships, while operationally valuable, significantly increase the attack surface and are often poorly understood or monitored by traditional identity and access controls.
Third-party SaaS risk typically arises from external services—often approved by users via OAuth—that gain broad or unnecessary permissions to core applications. A 2024 report by Onymos found that 45% of application development leaders reported a SaaS-related security incident through third-party integrations. Once connected, these tools operate with little to no human oversight and can persist long after their usefulness, exposing sensitive data or enabling lateral movement.
App-to-app risk usually stems from integrations created to streamline workflows, such as Salesforce pulling from Jira or a marketing automation platform syncing with Google Sheets. But they, too, can be over-permissioned, operate under stale credentials, or behave anomalously without tripping alerts. In one notable case, a modified Salesforce plugin with excessive API permissions exfiltrated sensitive customer data across multiple tenants, going undetected for weeks due to limited insight into app-to-app communication patterns and token scope usage.
Mitigating both forms of risk requires:
- A complete map of all third-party apps with access to core SaaS platforms. This includes every connected app authorized via OAuth, API key, or marketplace integration. Without a unified inventory, security teams cannot identify or evaluate potential vulnerabilities.
- Contextual analysis of granted permissions vs. actual usage. Security posture improves when you align what an app can do with what it actually does. For instance, integrations granted admin rights that only perform read operations should be flagged and downgraded.
- Automatic revocation of dormant or high-risk integrations. Connections that haven’t been used within a defined timeframe should be automatically revoked or escalated for review. This includes both unused third-party tools and inactive app-to-app tokens within enterprise workflows.
- Alerts for unusual data transfers or access spikes by third-party or connected apps. Excessive data pulls, off-hours access, or changes in behavior by known integrations should trigger alerts. These behaviors are strong indicators of token misuse or app compromise, especially when targeting machine-to-machine workflows.
At Wing Security, we treat app-to-app access with the same rigor as user access. Our platform continuously monitors all OAuth and API-based interactions, both external and internal, to enforce Zero Trust SaaS principles at the integration layer. Learn more in our post on third-party SaaS.
SaaS-specific threat detection in a Zero Trust model
Even with rigorous access controls and policy enforcement, threats can—and will—slip through. This is especially true in SaaS environments, where the attack surface is not confined to endpoints or internal networks, but distributed across cloud-native platforms with decentralized identity management and API exposure. That’s why Zero Trust SaaS must include purpose-built threat detection that understands the nuances of SaaS interactions at the telemetry level.
Traditional SIEMs and EDRs were designed for infrastructure-centric environments and struggle to parse SaaS-specific indicators. They typically lack native integration with SaaS apps and can’t detect behaviors like anomalous OAuth grants, token misuse, or privilege escalation within a collaborative tool’s UI. For example, a mass document export from Google Drive or an unexpected API token issuance in Salesforce might look like business as usual in a generic log stream, but represent high-risk behavior in context.
Effective SaaS threat detection requires telemetry from within the SaaS platform itself, including audit logs, permission change histories, login metadata, and API activity. These signals must be correlated in real-time and enriched with identity data to detect lateral movement, insider threats, or compromised integrations. A well-configured detection system should distinguish between a finance team’s regular batch report pull and a service account suddenly querying PII outside of its expected scope or timeframe.
According to the 2024 Microsoft Digital Defense Report, “22% of organizations had an attack path identified in the cloud,” while “40% of attack paths include lateral movement based on non-interactive remote code execution.” These often manifest not as overt intrusions but as subtle misuses of legitimate access. A common tactic involves incremental data exfiltration using syncing tools like Dropbox or Google Drive, or gradually modifying access rules and sharing settings to escalate privileges or expose sensitive resources.
To detect these behaviors with high fidelity, SaaS-native threat detection must include:
- Behavioral baselining and anomaly detection across apps
By building statistical models of normal user, group, and app-to-app behavior across tools like Slack, Salesforce, and Atlassian, anomalies, like an HR user accessing engineering repositories, can be flagged in real time. - Detection of suspicious permission changes or token activity
Alerting on privilege escalations (e.g., a user gaining admin access) or atypical token usage patterns (like API calls from new IPs or geolocations) is essential. Tokens that show sudden increases in scope usage or access frequency should be automatically investigated or revoked. - Integration with identity providers to correlate user sessions with alerts
Linking SaaS activity with identity provider telemetry (e.g., Okta, Azure AD) allows you to validate whether a session is tied to a known device, risk-flagged IP, or behavioral deviation. This adds valuable context and suppresses noise from benign anomalies. - Automated playbooks for containment and response
Once a threat is confirmed or highly probable, the system should automatically execute predefined actions such as revoking sessions, disabling tokens, alerting the SOC, or triggering downstream investigations. This minimizes dwell time and removes manual bottlenecks from the response workflow.
This isn’t just theory. In early 2024, Microsoft disclosed that the Midnight Blizzard threat group exploited a non-production Microsoft 365 tenant by password-spraying a user account without MFA. The attackers then abused a legacy OAuth application with broad privileges to access production email and created malicious OAuth apps to further their access. By using residential proxies, they masked their movements and evaded detection. This incident revealed how overprivileged OAuth apps and unmanaged machine identities can be leveraged in SaaS environments to bypass Zero Trust controls, especially when inter-app access is unmonitored.
As Zero Trust evolves, SaaS detection and response (SDR) becomes a required capability. At Wing, we integrate SaaS-native telemetry, identity signals, and behavioral context to deliver actionable threat detection built specifically for the cloud app layer. Explore our SDR capabilities to see how we’re helping security teams close the loop from visibility to enforcement.
SaaS visibility as the Zero Trust foundation
The Zero Trust model has become the cornerstone of modern cybersecurity frameworks. But for organizations that rely heavily on SaaS, Zero Trust cannot succeed without deep, continuous visibility and control over the cloud applications, integrations, and identities operating across the environment.
Zero Trust SaaS isn’t just a matter of enforcing traditional IAM or network segmentation in the cloud. It requires granular telemetry from SaaS platforms, real-time analysis of identity behavior, and continuous policy enforcement that adapts to shifting access patterns. This includes tracking OAuth token issuance and scope drift, detecting anomalous activity across service accounts, and correlating access attempts with device posture and user risk scoring.
Visibility without enforcement leads to alert fatigue and exploitable gaps. Conversely, enforcing policies without sufficient visibility risks breaking workflows and failing to detect sophisticated lateral movement. Effective Zero Trust SaaS means having both a real-time, feedback-driven model that integrates identity, device and SaaS-layer context to dynamically manage access and detect threats.As SaaS adoption accelerates and app-to-app interconnectivity deepens, threats will continue to grow more complex and indirect. Only by combining automated SaaS discovery, contextual access control, and SaaS-native threat detection can organizations ensure that Zero Trust becomes a continuously enforced operational reality.